How is neural architecture search performed?
You could say that NAS fits into the domain of Meta Learning or Meta Machine learning.

I've pulled the NAS papers from my notes, this is a collection of papers/lectures that I personally found very interesting. It's sorted in rough chronological descending order, and *** means influential / must read.

Quoc V. Le and Barret Zoph are to good authors on the topic.


The Evolved Transformer
Exploring Randomly Wired Neural Networks for Image Recognition
GRAPH HYPERNETWORKS FOR NEURAL ARCHITECTURE SEARCH
Backprop Evolution
Progressive Neural Architecture Search
*** DARTS: Differentiable Architecture Search
*** Efficient Neural Architecture Search via Parameter Sharing - ENAS
*** Progressive Neural Architecture Search
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search
Automatic Machine Learning - Prof. Frank Hutter
Google Brain - Neural Architecture Search - Quoc Le
*** Regularized Evolution for Image Classifier Architecture Search
Autostacker: A Compositional Evolutionary Learning System
Generating Neural Networks with Neural Networks
Finding Competitive Network Architectures Within a Day Using UCT
Neuroevolution: A different kind of deep learning
Evolving Deep Neural Networks
Pieter Abbeel: Deep Learning-to-Learn Robotic Control
*** SMASH: One-Shot Model Architecture Search through HyperNetworks